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首页> 外文期刊>Water >Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China
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Landslide Susceptibility Mapping in Vertical Distribution Law of Precipitation Area: Case of the Xulong Hydropower Station Reservoir, Southwestern China

机译：降水区垂直分布规律中的滑坡敏感性图-以西南地区徐龙水电站水库为例

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This study focused on landslide susceptibility analysis mapping of the Xulong hydropower station reservoir, which is located in the upstream of Jinsha River, a rapidly uplifting region of the Tibetan Plateau region. Nine factors were employed as landslide conditioning factors in landslide susceptibility mapping. These factors included the slope angle, slope aspect, curvature, geology, distance-to-fault, distance-to-river, vegetation, bedrock uplift and annual precipitation. The rapid bedrock uplift factor was represented by the slope angle. The eight factors were processed with the information content model. Since this area has a significant vertical distribution law of precipitation, the annual precipitation factor was analyzed separately. The analytic hierarchy process weighting method was used to calculate the weights of nine factors. Thus, this study proposed a component approach to combine the normalized eight-factor results with the normalized annual precipitation distribution results. Subsequently, the results were plotted in geographic information system (GIS) and a landslide susceptibility map was produced. The evaluation accuracy analysis method was used as a validation approach. The landslide susceptibility classes were divided into four classes, including low, moderate, high and very high. The results show that the four susceptibility class ratios are 12.9%, 35.06%, 34.11%and 17.92% of the study area, respectively. The red belt in the high elevation area represents the very high susceptibility zones, which followed the vertical distribution law of precipitation. The prediction accuracy was 85.74%, which meant that the susceptibility map was confirmed to be reliable and reasonable. This susceptibility map may contribute to averting the landslide risk in the future construction of the Xulong hydropower station.
机译：该研究的重点是位于金沙江上游的徐龙水电站水库的滑坡敏感性分析图，金沙江是青藏高原地区一个迅速隆升的地区。在滑坡敏感性地图中，将九个因素用作滑坡条件因素。这些因素包括坡度角，坡度，曲率，地质，断层距离，河流距离，植被，基岩隆起和年降水量。基岩快速抬升因子由倾斜角表示。使用信息内容模型处理了八个因素。由于该地区的降水量垂直分布规律显着，因此分别分析了年降水量因子。运用层次分析法加权计算九个因子的权重。因此，本研究提出了一种将归一化八因子结果与归一化年降水量分布结果相结合的分量方法。随后，将结果绘制在地理信息系统（GIS）中，并绘制了滑坡敏感性图。评估准确性分析方法用作验证方法。滑坡敏感性等级分​​为低，中，高和极高四个等级。结果表明，四种药敏率分别为研究区域的12.9％，35.06％，34.11％和17.92％。高海拔地区的红带代表着很高的磁化率带，其遵循降水的垂直分布规律。预测准确性为85.74％，这表明敏感性图被证实是可靠合理的。该敏感性图可能有助于避免在徐龙水电站的未来建设中发生滑坡风险。

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